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SalaryJob Description
About the company:
Founded in the early 2000s, the digital healthcare marketing agency is dedicated to enhancing HCP engagement. Our client's team boasts over 120 marketing experts who possess in-depth knowledge of the ever-evolving healthcare landscape, intricate content, and the strategic use of data to achieve significant results. Their continuous achievements are a result of their proficiency in omnichannel strategies and a comprehensive range of digital services, including Account Services, Creative, Digital and Brand Strategy, Digital Production and Project Management, 3D Animation, Digital Development, and Video production.
Job Responsibilities:
- Create Extraction Models using document processing products (Advanced Designer, Vantage): This involves using software to design and implement extraction models for various document types.
- Comprehensive Document Analysis: Conduct in-depth analysis of documents based on provided requirements. This may include classifying, sorting, and generalizing document layouts to improve extraction accuracy.
- Creating Requirements for Document Labelling: Define the labeling requirements for documents and manage the labeling process. This is crucial for training and improving the accuracy of extraction models.
- Creating Flexible Descriptions using Metalanguage: Utilize a document processing tool to create flexible document descriptions using metalanguage, as described in the provided link. This is a key part of designing extraction models.
- Training Neural Network: Possibly involved in training neural networks to enhance the performance of document extraction models.
- Strong Analytical Skills: Ability to analyze documents, requirements, and data to design effective extraction models.
- Basic Understanding of Data Formats (XML, JSON, and CSV): Familiarity with common data formats for document processing.
- Command Line and PowerShell Proficiency: Proficiency in using command line interfaces and PowerShell for automation and scripting.
- Experience with Git: Knowledge of version control systems like Git for collaborative software development.
- Readiness to Acquire New Information: Willingness and ability to learn new information and adapt to changing technologies and requirements.
- Capacity to Comprehend Novel Content: Ability to understand complex and unfamiliar content.
- Ability to Organize Substantial Volumes of Data: Effective organization and management of large datasets.
- Team Collaboration: Ability to work effectively within a team, as indicated by the requirement for collaboration.
As an advantage:
- Basic Knowledge of Programming: Familiarity with programming concepts may be advantageous for working with extraction models and automation.
- 8+ years of experience in Data Engineering and Big Data: The ideal candidate should have substantial hands-on experience in the field.
- Proven work experience with ETL Development or similar areas: Experience in Extract, Transform, Load (ETL) processes or related data integration tasks is necessary.
- Advanced knowledge in Database Engines, Data Lakes, Data Practices, and policies: A deep understanding of various database technologies, data lakes, and industry best practices is expected.
- In-depth understanding of database structure principles, integration, ETL, ELT, data processing, and data management: Proficiency in database principles, ETL/ELT concepts, data processing, and data management is crucial.
- Hands-on experience with programming languages: Proficiency in programming languages such as Python, Java, Scala, and SQL is necessary for building data pipelines and performing data analysis.
- Experienced in assembling large, complex data sets: The candidate should be able to gather and work with large and complex datasets that fulfill both functional and non-functional business requirements.
- Experienced in building the infrastructure for data extraction, transformation, and loading: Building the necessary infrastructure for efficient data extraction, transformation, and loading from various data sources is a key skill.
- Bachelor's degree in a related field: A bachelor's degree in a relevant field is typically a minimum educational requirement.
- Analytical skills and strong organizational abilities: Strong analytical skills and organizational abilities are essential for effective data engineering.
Additional Perks:
- Flexible and remote working options to accommodate different lifestyles.
- Flexible working hours to support work-life balance.
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